Each year, crime data geeks look forward to the publication of the CJIS “Crime in the United States” report. On September 30th, the FBI was able to share the Uniform Crime Report information for 2018, describing information about Violent Crime, Property Crime, Homicides, and Arrests gathered from most of the law enforcement agencies in the United States. UCR is old news though. Many short-comings in the system have led to changes which are adopted in the new NIBRS system, the National Incident-Based Reporting System. For people like me, who care about cybercrime, hacking, malware, and fraud, this is great news! Many budget decisions have been made over the years about how to allocate police resources based on UCR data, and NONE OF THE CATEGORIES I CARE ABOUT WERE PART of UCR! But NIBRS has many of those things, rolled up under the category “fraud.”
- 26A = False Pretense / Swindle / Confidence Game
- 26B = Credit Card / ATM Fraud
- 26C = Impersonation
- 26D = Welfare Fraud
- 26E = Wire Fraud
- 26F = Identity Theft
- 26G = Hacking / Computer Invasion
With shame, I mention that Alabama is one of the states boycotting NIBRS, calling it an “unfunded mandate” and refusing to participate. In the 2017 data, only the city of Hoover shared NIBRS-formatted crime statistics with the Department of Justice. (Hopefully we will see an improvement in this process as Alabama is now one of the states receiving federal funding to improve their NIBRS participation in the form of an NCS-X Initiative Grant. In October 2018, an additional $49 Million was released to encourage greater participation. A sampling study was conducted by BJS to determine that if 400 additional agencies were added, it would have a marked improvement of the accuracy and usefulness of NIBRS data, and these agencies and their states are now targeted, for the fourth year in a row, with Federal funding to assist in implementation. Eleven Alabama Law Enforcement agencies were among the 400 on the “List of NCS-X Sample Agencies as of August 2018” making them eligible to apply for funding. Only four states have not received any funding to date – AK, AZ, MS, and NM. Sixteen states have fully implemented NIBRS, and four more have >80% participation.)
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| https://ucr.fbi.gov/ucr-statistics-their-proper-use |
A caution before reading on, despite the FBI’s repeated warning to not use crime data to rank jurisdictions, journalists repeatedly put out reports called things like “The Top Worst Cities for Murder” each year after the UCR is released. In the table below, we have extracted the FBI data for Fraud Arrests for each of their 56 field offices. This is intended to show how fraud arrests (including all of the categories above) are still a MINOR focus of law enforcement by proportion of arrests, so PLEASE don’t use this data to rank. (More reasons not to rank in the link above, which is labeled “Caution Against Ranking” on the Crime in the United States page.
As part of that caution, consider a couple numbers from the table below. While the average for all field offices was that 10.9% of all FBI arrest in 2018 were for “Fraud” categories, the Los Angeles Field Office number was more than double that amount, at 27.6%. Why? Is it because there is more fraud in LA than most places? Not really. Their “Fraud Arrests per 100,000 population” is 1.4, nearly double the national average of 0.8. Los Angeles serves the largest population of any field office — 19.5 million people — allowing their office composition to contain specialized squads not found in smaller offices. One such squad includes agents dedicated to working “Business Email Compromise” and they have been doing an amazing job at that task. Because of the STRATEGIC FOCUS of the Los Angeles office, many criminals are arrested and charged there even when the victims may come from across the United States and the World.
Similarly, the Miami, District of Columbia, and New York offices have significantly higher fraud arrest rates per 100,000 populations than other offices. This also reflects the composition of their offices. New York City FBI arrested 1,466 total people in 2018 — nearly 500 more than any other office, and triple the number of the arrests in only slightly smaller Dallas, Boston, Atlanta, or Charlotte. As a global super power in the banking world, New York City has one of the largest cybercrime offices in the country, including many New York Police Department personnel who serve as Task Force Officers within the FBI’s Cybercrime and Financial Crime Task Forces. In offices like NYC, many cases where a local prosecution may have been brought elsewhere by the police have been elevated to a federal level, taking advantage of the unique concentration of banks AND FEDERAL RESOURCES, to make possible their 268 fraud arrests in a field office serving 13.4 million people. Similar combined state/local/federal task forces raise their arrest rate in other categories, partly as a result of the unique partnerships found in New York as a result of the restructuring of the FBI following the terrorist attacks there on 9/11.
Other office numbers may be skewed by the presence of an extremely gifted or well-funded state or local law enforcement agencies, which may work many cases at the state/local level that in other offices may have become federal cases.
(Crime rate per 100,000 is ((Arrests / Population) x 100,000), for example, in NYC, (268/13,464,042 = 0.000019904 * 100,000 = 1.99 (rounded to 2.0) per 100,000 population.)
| Field Office | Fraud Arrests | Total Arrests | Population | % Fraud Arrests | Fraud arrests per 100k population |
|---|---|---|---|---|---|
| Grand Total All Offices | 2,645 | 24,174 | 330,611,016 | 10.9% | 0.8 |
| Albany | 19 | 193 | 3,959,142 | 9.84% | 0.5 |
| Albuquerque | 11 | 368 | 2,095,428 | 2.99% | 0.5 |
| Anchorage | 3 | 110 | 737,438 | 2.73% | 0.4 |
| Atlanta | 86 | 635 | 10,519,475 | 13.54% | 0.8 |
| Baltimore | 20 | 397 | 7,009,889 | 5.04% | 0.3 |
| Birmingham | 16 | 153 | 2,885,679 | 10.46% | 0.6 |
| Boston | 78 | 515 | 10,654,326 | 15.15% | 0.7 |
| Buffalo | 28 | 318 | 2,745,324 | 8.81% | 1.0 |
| Charlotte | 22 | 548 | 10,383,620 | 4.01% | 0.2 |
| Chicago | 72 | 399 | 9,299,342 | 18.05% | 0.8 |
| Cincinnati | 23 | 257 | 5,973,003 | 8.95% | 0.4 |
| Cleveland | 40 | 426 | 5,716,439 | 9.39% | 0.7 |
| Columbia | 25 | 313 | 5,084,127 | 7.99% | 0.5 |
| Dallas | 42 | 556 | 10,937,892 | 7.55% | 0.4 |
| Denver | 55 | 400 | 6,273,301 | 13.75% | 0.9 |
| Detroit | 132 | 762 | 9,995,915 | 17.32% | 1.3 |
| El Paso | 13 | 217 | 1,280,400 | 5.99% | 1.0 |
| Honolulu | 19 | 92 | 1,420,491 | 20.66 | 1.3 |
| Houston | 45 | 348 | 8,739,890 | 12.93% | 0.5 |
| Indianapolis | 63 | 541 | 6,691,878 | 11.65% | 0.9 |
| Jackson | 19 | 230 | 2,986,530 | 8.26% | 0.6 |
| Jacksonville | 42 | 129 | 5,292,491 | 32.56% | 0.8 |
| Kansas City | 21 | 572 | 6,107,812 | 3.67% | 0.3 |
| Knoxville | 16 | 413 | 2,634,746 | 3.87% | 0.6 |
| Las Vegas | 13 | 294 | 3,034,392 | 4.42% | 0.4 |
| Little Rock | 11 | 209 | 3,013,825 | 5.26% | 0.4 |
| Los Angeles | 270 | 978 | 19,503,778 | 27.61% | 1.4 |
| Louisville | 17 | 177 | 4,468,402 | 0.96% | 0.4 |
| Memphis | 35 | 292 | 4,135,264 | 11.99% | 0.8 |
| Miami | 241 | 1048 | 7,101,580 | 0.23% | 3.4 |
| Milwaukee | 28 | 180 | 5,813,568 | 15.56% | 0.5 |
| Minneapolis | 35 | 620 | 7,253,491 | 5.65% | 0.5 |
| Mobile | 14 | 196 | 2,002,192 | 7.14% | 0.7 |
| New Haven | 24 | 315 | 3,572,665 | 7.62% | 0.7 |
| New Orleans | 13 | 234 | 4,659,978 | 5.56% | 0.3 |
| New York | 268 | 1466 | 13,464,042 | 18.28% | 2.0 |
| Newark | 55 | 533 | 8,055,342 | 10.32% | 0.7 |
| Norfolk | 15 | 108 | 1,759,484 | 13.89% | 0.9 |
| Oklahoma City | 20 | 252 | 3,943,079 | 7.94% | 0.5 |
| Omaha | 10 | 294 | 5,085,413 | 0.34% | 0.2 |
| Philadelphia | 106 | 723 | 9,948,745 | 14.66% | 1.1 |
| Phoenix | 34 | 773 | 7,171,646 | 0.44% | 0.5 |
| Pittsburgh | 40 | 543 | 5,517,325 | 7.37% | 0.7 |
| Portland | 32 | 303 | 4,190,713 | 10.56% | 0.8 |
| Richmond | 10 | 110 | 4,153,705 | 9.09% | 0.2 |
| Sacramento | 33 | 298 | 8,099,068 | 11.07% | 0.4 |
| Salt Lake City | 53 | 606 | 5,977,618 | 8.75% | 0.9 |
| St. Louis | 26 | 422 | 2,930,145 | 6.16% | 0.9 |
| San Antonio | 36 | 879 | 7,743,663 | 0.41% | 0.5 |
| San Diego | 33 | 384 | 3,529,064 | 8.59% | 0.9 |
| San Francisco | 71 | 342 | 8,425,135 | 20.76% | 0.8 |
| San Juan1 | 40 | 716 | 3,443,582 | 5.59% | 1.2 |
| Seattle | 34 | 359 | 7,535,591 | 9.47% | 0.5 |
| Springfield | 12 | 157 | 3,441,738 | 7.64% | 0.3 |
| Tampa | 30 | 800 | 8,905,254 | 3.75% | 0.3 |
| Washington, Dc | 76 | 671 | 3,306,951 | 11.33% | 2.3 |
*** This is a Security Bloggers Network syndicated blog from CyberCrime & Doing Time authored by Gary Warner, UAB. Read the original post at: http://garwarner.blogspot.com/2019/10/fbi-fraud-arrests-by-field-office-2018.html



